import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PlateAnalysis_Echo import PlateDataset
from tqdm import tqdm

dataset = PlateDataset('20191104_Dopt.CSV','D_Opt.csv')


output =  pd.DataFrame([],columns = [ 'K','percentDMSO', 'Vol','km', 'vmax', 'loss', 'r_squared'])
for i in tqdm(range(1,19)):
    output=output.append(dataset.CalculateMetrics(i))
    
output = output.reset_index(drop=True)
output.to_csv('DOptExperimnentResults.csv')
output

100%|██████████| 18/18 [00:13<00:00,  1.33it/s]

for i in range(1,19):
    dataset.PlotFigure(i)

	K	percentDMSO	Vol	km	vmax	loss	r_squared
0	1.000000	5.000000	20.0	2.477096	0.043018	0.007542	0.358127
1	2.636364	3.181818	20.0	2.562310	0.038098	0.010789	0.570633
2	4.000000	1.000000	20.0	1.262799	0.060722	0.001688	0.989200
3	4.000000	1.000000	20.0	2.656589	0.056360	0.005327	0.906591
4	1.545455	1.000000	20.0	2.345846	0.028151	0.012497	0.385633
5	1.000000	5.000000	20.0	2.057473	0.014975	0.012475	0.071120
6	2.636364	3.181818	20.0	0.209351	0.057884	0.027953	-0.043036
7	2.636364	5.000000	29.0	3.000489	0.054683	0.005098	0.804826
8	2.636364	5.000000	29.0	3.316767	0.076424	0.018771	0.468825
9	1.000000	2.818182	29.0	2.266800	0.035202	0.024059	0.154214
10	1.000000	2.818182	29.0	3.246844	0.086234	0.005716	0.942767
11	1.000000	5.000000	40.0	3.214294	0.076385	0.014323	0.369197
12	1.000000	1.000000	40.0	2.029973	0.016484	0.046828	-0.378452
13	4.000000	5.000000	40.0	1.482239	0.014382	0.026557	-0.145138
14	1.000000	5.000000	40.0	3.143757	0.073450	0.029190	0.141555
15	1.000000	1.000000	40.0	2.183681	0.024263	0.025474	-0.017859
16	4.000000	1.000000	40.0	0.039473	0.105401	0.004752	0.965356
17	4.000000	1.000000	40.0	0.901144	0.109199	0.004858	0.979317